History

History

Waveform Information Vector (WIV) waveform analysis is a 40-year-old ‘new’ technology that you have probably never heard of.  Envisioned by the electrical engineer John Bates as a technique to uniquely identify and determine the direction of hostile radar sources. It was a clever trick, first employed as a hardware solution, and its underlying technology – the clever bit – was hidden in a schematic diagram and classified.  Once declassified, it emerged as a hardware solution in a period when computers and frequency-based Fourier analysis dominated waveform analysis.  It was ignored at the time and eventually forgotten by all – except by its creator, John K. Bates.

Bates knew one fact overlooked by many others – it is an analog of the human cochlear.  His first application uniquely identified individual radar sources by noting the slight differences in each’s radar signal.   It identified the location of each source by measuring the slight differences in the time of arrival at two separated detectors.  It’s no stretch of the imagination to see the similarity between locating radar sources and locating individual voices in a room.

Over the last 40 years, John converted the WIV logic to software and used in understanding the cochlea – vocalization and speech recognition.  and created applications for waveform analysis and speech recognition.   study the cochlea’s properties.  Much of his work has been extensively published.  During this period, the code was improved, reduced in size and increased in processing speed.

Chris Shafer, a long term colleague of Bates and WIV application developer, incapsulated the WIV processor’s logic in an Assembly Language module for the IBM 8088 computer. In the ensuing years, John and Chris continued to work on the WIV technology and in the 1990’s Chris improved the original application’s logic and ported it to C++.  It was during this time that Albert Doolittle, a computer technology expert became interested in WIV processing and encouraged its further development.

Early in 2008, Chris demonstrated his C++ real-time WIV processor to vocal training expert Katarina Bordeaux.  She immediately recognized the potential of WIV processing as an aid for teaching her voice students.  Through a series of meetings in 2008 Chris, John, Katarina, and Al formed WIV LLC. And produced its first commercial product – Passaggio, a vocal training system for use by singing coaches and individual singers.  Passaggio was later converted to an Apple iOS application.

More recent work has focused on developing custom waveform analysis modules for researchers and industries needing high-speed, real-time waveform analysis in high noise environments.

Waveform Information Vector (WIV) waveform analysis is a 40-year-old ‘new’ technology.  Created during the cold war as a technique to uniquely identify and determine the direction of hostile radar sources, it was first employed as a hardware solution with the underlying technology hidden in the lines of a schematic diagram – and classified.  Once declassified, it emerged as a hardware solution at a period when computers and frequency-based Fourier analysis dominated waveform analysis.  It was ignored at the time and eventually forgotten by all – except by its creator, John K. Bates.

John’s solution used a clever, simple approach to the problem.     was an out-of-the-box solution John knew something about the WIV technology that became apparent during its early creation – it was an analog of the human cochlea.  Over the last 40 years, John converted the logic to software and used in understanding the cochlea and created applications for waveform analysis and speech recognition.   study the cochlea’s properties.  Much of his work has been extensively published.  During this period, the code was improved, reduced in size and increased in processing speed.

Now retired, John has worked in the corporate world and on his own as an engineer and researcher. Two of his companies, Time/Space Systems and VOIS, Inc., were partially funded by government grants to develop his Wave Information Vector (WIV) signal processing technology.

At VOIS, Chris Shafer developed a real-time WIV processor in Assembly Language on the IBM 8088. In the ensuing years, John and Chris continued to work on the WIV technology and in the 1990’s Chris improved the original application and ported it to C++.  It was during this time that Albert Doolittle, a computer technology expert became interested in WIV processing and encouraged its development.

Early in 2008, Chris demonstrated his C++ real-time WIV processor to vocal training expert Katarina Bordeaux.  She immediately recognized the potential of WIV processing as an aid for teaching her voice students.  Through a series of meetings in 2008 Chris, John, Katarina, and Al participated in organizing WIV LLC. By 2009 the Passaggio vocal training system was operational and beta tested. It has been so successful that Katarina uses it regularly as one of her major tools with her students.

WIV LLC intends to continue the development of WIV technology through continued research and real-world applications.

We believe our technology will eventually find its way into many applications that currently rely on spectral analysis.

The core of Bates’ clever trick is a particle-like Waveform Information Vector (WIV). WIV particles are created at the instance of a ‘time event’ (waveform crossing, etc.) and encapsulates the time, space, and energy information necessary to make it possible to recognize, separate, locate, and understand the sounds in the auditory scene.  WIV’s time-based particles preserve sufficient acoustic information to permit the reconstruction of a waveform using particles alone.  Furthermore, WIV’s event timestamps are real-time and are of sufficient precision to make them capable of determining the direction of a sound when being used in a binaural configuration – just like our ears.   Being particles, noise reduction is performed by removing particles, not filtering out frequencies.  This has the added benefit of being able to remove noise buried underneath a tone without affecting the tone itself.  Lastly, and one suggesting future applications – the WIV processor is simple enough to successfully run in real-time using iOS-based devices and microcontrollers such as a Raspberry Pi.

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